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Interleukin-17 (IL-17) is an important cytokine that plays a critical role in the inflammatory response and host defense against extracellular pathogens. In the present study, six novel IL-17 family genes (MaIL-17) were identified by analyzing Asian swamp eel (Monopterus albus) genome. Sequence analysis revealed that the MaIL-17 family genes shared similar features, comprising a signal peptide, an IL-17 superfamily region, and four conserved cysteines. Phylogenetic analysis showed that the MaIL-17 genes were clustered together with their corresponding IL-17 genes from other species. The similarity and identity of all IL-17 family genes indicated that the MaIL-17 genes are conserved among teleosts, while Ma-IL-17D is more conserved than the other Ma-IL-17s. Except for MaIL-17A/F3 and MaIL-17D, all MaIL-17s shared the same genomic structure as the genes from other fish, namely three exons and two introns. The MaIL-17s showed conserved synteny among fish, and we found that the MaIL-17D locus has a more conserved syntenic relationship with the loci from other fish and humans. These results demonstrated that MaIL-17D and human IL-17D might have evolved from a common ancestral gene and subsequently diverged. The analysis of swamp eel reference genes revealed that EEF1A1 (encoding eukaryotic translation elongation factor 1 alpha 1) was an ideal reference gene for accurate real-time qRT-PCR normalization in the swamp eel. The MaIL-17 genes are widely distributed throughout tissues, suggesting that MaIL-17s carry out their biological functions in immune and non-immune tissues compartments. The transcript of Ma-IL17s exhibited different fold changes in head kidney cells in response to Aeromonas veronii phorbol 12-myristate 13-acetate (PMA) and polyinosinic:polycytidylic acid (poly I:C) challenge, showing that MaIL-17A/F1 has stronger antiviral activities compared with other MaIL-17 family genes, and that MaIL-17A/F3 and MaIL-17A/F2 possess stronger effects against extracellular pathogens compared with the others; however, MaIL-17C2 and MaIL-17D may play vital roles during pathogen infection. The differential immune responses of these genes to Aeromonas veronii, PMA and poly I:C implied distinct mechanisms of host defense against extracellular pathogens.

Pose and illuminations remain great challenges to current face recognition technique. In this paper, visible image (VI) and near-infrared image (NIR) are fused for performance improvement. When directional binary code is adopted as feature representation, AdaBoost algorithm and the cascade structure are used for classification. Fusion is done at decision level and classification scores are normalized using three different rules, i.e. Min-Max, Z-Score and Tanh-Estimators. Experimental results suggest that the proposed algorithm using VI achieve better performance than NIR when pose and expression variations are present. However, NIR shows much better robustness against illumination and time difference than VI. Due to the complementary information available in two image modalities, fusion of NIR and VI further improves the system performance.